get_K: Construct Bias Penalisation

In ICBioMark: Data-Driven Design of Targeted Gene Panels for Estimating Immunotherapy Biomarkers

Description

An internal function, producing the correct bias penalisation for use in predictive model fitting.

Usage

get_K(
  gen_model,
  p_norm,
  training_matrix,
  marker_training_values = NULL,
  method = max
)

Arguments

gen_model	(list) A generative mutation model, fitted by fit_gen_model().
p_norm	(numeric) Scaling factor between coefficients of p and parameters of generative model (see paper for details).
training_matrix	(sparse matrix) A sparse matrix of mutations in the training dataset, produced by get_mutation_tables().
marker_training_values	(dataframe) A dataframe containing training values for the biomarker in question.
method	(function) How to select a representative biomarker value from the training dataset. Defaults to max().

Value

A numerical value, to be used as a penalty weighting in the subsequent group lasso optimisation.

Examples

K <- get_K(example_gen_model, 1, example_tables$train$matrix)
print(K)

ICBioMark documentation built on Nov. 15, 2021, 5:09 p.m.